Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
661-03-013 ISMRM Abstract

Deep learning based correction of FID artifacts in SPACE imaging

Primary: Acquisition & Reconstruction - Artifacts and Correction Strategies
Secondary: Acquisition & Reconstruction - AI methods
661-03-013 · Noise and Artifact Mitigation in MRI · Thursday, 14 May, 1:40 PM–2:35 PM · Digital Posters Row B
Keywords: Deep learning SPACE FID artifact Turbo Spin-Echo (TSE)
Accepted
Hanna Wichtel 1,2,3, Hans-Peter Fautz2,3, Dominik Paul2, Florian Putz4, Jana Hutter5
1Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
2Siemens Healthineers AG, Erlangen, Germany
3Imaging Science Institute, Erlangen, Germany
4University Hospital Erlangen (UKER), Erlangen, Germany
5Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
Presenting Author: Hanna Wichtel

Synopsis

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References

1. Mugler III, John P. "Optimized three‐dimensional fast‐spin‐echo MRI." Journal of magnetic resonance imaging 39.4 (2014): 745-767. https://doi.org/10.1002/jmri.24542 [doi]
2. Ahn, Sangtae, Anne Menini, and Christopher J. Hardy. "A deep network for reconstruction of undersampled fast-spin-echo MR images with suppressed fine-line artifact."
3. O. Ronneberger, P. Fischer, and T. Brox, “U-Net: Convolutional networks for biomedical image segmentation,” in Proc. Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2015, pp. 234–241. doi:10.1007/978-3-319-24574-4_28 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/661-03-013